Kalman Filtering the Yaw Pitch Roll data from MPU6050

Hello everyone, I am currently working on a self balancing robot project. I currently have my code to get Yaw Pitch and Roll data from the MPU6050 by using the MPU6050_6Axis_MotionApps20 library. With the help of this library I do not need to work with dependent variables such as GyroX, GyroY, GyroZ, AccX etc.

My question is, can I apply Kalman Filter to these 3 variables only? I have looked up in Internet but everyone that used Kalman Filter for MPU6050 had variables that I dont use.

Thanks a lot in advance.

Yes, and the result will be very similar to a moving average. There is no benefit.

jremington: Yes, and the result will be very similar to a moving average. There is no benefit.

What do you mean? The data I get is already accurate and I dont need to filter it?

The data that you get from any consumer grade IMU are NOT very accurate, guaranteed. And only then if you have carefully calibrated all of the sensors.

A Kalman filter on each of the angles will only average out random noise, like any other averaging process.

jremington: The data that you get from any consumer grade IMU are NOT very accurate, guaranteed. And only then if you have carefully calibrated all of the sensors.

A Kalman filter on each of the angles will only average out random noise, like any other averaging process.

Yes, thank you. But I do know that.

My question is, can I still apply the Kalman Filter for 3 variables instead of 6?

See reply #1